The Four Mistakes That Make AI Videos Look Fake (And the Fixes)
Liam's Cut
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The Four Mistakes That Make AI Videos Look Fake (And the Fixes)
47 просмотров · 1 месяц назад
Liam's Cut
33 подписчика
47 просмотров · 1 месяц назад
Four mistakes make AI video read as fake, and three of them have nothing to do with image quality. I deliver AI video to clients alone, I have cut my work against real footage for months, and the tell is rarely what people blame. The model is innocent.
Mistake one: letting the face drift. Take one is her, take ten is a different actress in the same jacket, because every generation starts from zero and re-imagines whatever you did not hand it. Mistake two: letting the room drift. The window trades walls, the counter swaps sides, a door appears, and nobody catches it consciously, they just say something feels off. Mistake three: letting the light move, when a real room has one sun and an AI room gets a new one per generation. Mistake four is the only craft one: too clean, zero grain, infinite focus, every shot the same length off a nailed tripod.
The fixes fit in one evening. Characters locked as sheets, locations generated four variations each at 16 by 9 and 4K, stills held at 2K even when the delivery is 1080p. Pick the most legible frame, where the light direction and the depth read.
invideo agent carries the locked sheets, plates and rules into every generation and re-runs any take that breaks them before you see it.
Then coverage: roughly 15-second generations cut as one scene, 24 fps, one lens family per scene. Premiere Pro for the cut, Topaz only if the spec demands it, grain after the grade.
https://invideo.io/
0:00 Why AI videos look fake before a client sees it
0:53 Cause one: the face changes
1:15 Cause two: the room changes
1:40 What has to hold before you generate anything billable
1:56 Build the character sheet
2:28 The second character, and wardrobe states
3:20 Locations: batch, legibility, lock the plate
3:49 Context: the rules a picture cannot carry
4:12 Generate, and attach nothing
4:25 The attachment panel
4:59 Cause three: the light
5:23 Cause four: too clean
5:38 Coverage: wide, close, reverse
6:39 The principle
8:27 The honest edge and the verdict
#invideo #aivideomistakes